Higher symbol (baud) rates are likely to be implemented in next-generation networks to provide data rates in excess of 100 Gigabits per second (Gbps) over relatively long distances, e.g., 500 kilometers or more. Some network components may be unable to support such high symbol rates without introducing significant distortion into the signal. One form of signal distortion is inter-symbol interference (ISI), which occurs when leading symbols interfere with trailing symbols. ISI typically results when a signal is communicated over a dispersive channel, which causes individual pulses of symbols in the signal to appear smeared and/or broadened upon reception. The source of ISI is largely medium dependent. In wireless channels, ISI is primarily attributable to multipath propagation, which occurs when the wireless signal traverses multiple paths between the transmitter and the receiver, e.g., as may result from the transmitted signal reflecting off boundaries such as the ground, bodies of water, and physical objects between the transmitter and receiver. In optical channels, ISI is primarily attributable to chromatic dispersion, which occurs when light traveling through the fiber exhibits different speeds at different wavelengths. Additionally, ISI may be attributable to the bandlimited nature of optical front-ends and various network elements, e.g., wavelength selective switches (WSS). Excessive ISI can cause errors during signal decoding at the receiver.
At the receiver, received signals are demodulated to determine a complex value associated with each symbol carried by the signal. The demodulated symbols are then decoded at the bit-level to determine binary values for each of the bits in each of the symbols. ISI may introduce errors into symbol demodulation by causing the received symbols to be mapped to the incorrect constellation point. This may, in turn, cause errors during bit-level decoding. To reduce bit error rates, soft-output information is often used as an input-parameter during bit-level decoding in conjunction with forward error correction (FEC). Soft-output information may be generated from symbol demodulation and/or equalization, and often includes log likelihood ratios (LLRs), which are values that indicate how many times more likely a bit is to be one binary value than the other binary value. LLRs may be particularly prevalent in communications systems that employ iterative forward error correction (FEC) encoding schemes. In particular, FEC encoding introduces redundancy in the transmitted data which can be leveraged by the receiver by means of FEC decoding to lower the error rates of the transmitted data to desired levels. In most high performance FEC designs, the decoder invariably accepts soft information that is iteratively refined over certain cycles of the FEC processing.